Data prediction is a useful tool with applications for a variety of industries. Examples of data prediction include predicting a next bit in a sequence of bits, or a next value in a sequence of values. Such data prediction techniques may have a variety of uses and applications including predicting future load on computing devices, predicting future prices of stocks and commodities, and predicting click-through rates for online advertisements, for example.
An objective of data prediction is to predict data with a high accuracy and a low overall loss. The loss of a data prediction algorithm is a measure of the number of times the algorithm predicts a data value correctly versus the number of times the algorithm predicts a data value incorrectly. Current methods for data prediction are deficient with respect to both accuracy and overall loss.